Notebook
In [4]:
"""
Rotate between S&P 500, mid-cap value, small cap international, emerging markets, and intermediate treasuries
    Use momentum (short term moving average ratio to long term)
$10K initial, with IB fees
"""
bt = get_backtest('58a10bac98a6065defa8d7b0')
bt.create_full_tear_sheet()
100% Time: 0:00:01|###########################################################|
Entire data start date: 2008-07-01
Entire data end date: 2016-12-30


Backtest Months: 102
Performance statistics Backtest
annual_return 0.14
cum_returns_final 1.96
annual_volatility 0.16
sharpe_ratio 0.89
calmar_ratio 0.53
stability_of_timeseries 0.80
max_drawdown -0.26
omega_ratio 1.17
sortino_ratio 1.29
skew 0.03
kurtosis 4.38
tail_ratio 1.05
common_sense_ratio 1.19
gross_leverage 1.00
information_ratio 0.01
alpha 0.11
beta 0.26
Worst drawdown periods net drawdown in % peak date valley date recovery date duration
0 25.67 2014-09-05 2016-01-08 NaT NaN
1 13.40 2010-04-23 2010-05-20 2010-10-05 118
2 11.85 2009-06-01 2009-06-23 2009-08-03 46
3 10.64 2009-10-19 2009-10-30 2009-11-16 21
4 9.35 2012-03-19 2012-05-18 2012-12-20 199

[-0.019 -0.037]
/usr/local/lib/python2.7/dist-packages/numpy/lib/function_base.py:3834: RuntimeWarning: Invalid value encountered in percentile
  RuntimeWarning)
Stress Events mean min max
Lehmann 0.03% -1.77% 1.88%
US downgrade/European Debt Crisis 0.17% -1.46% 1.55%
Fukushima 0.17% -1.07% 2.03%
EZB IR Event -0.01% -1.54% 1.61%
Sept08 0.01% -1.77% 1.88%
2009Q1 -0.10% -1.40% 1.63%
2009Q2 0.46% -4.87% 7.01%
Flash Crash -0.43% -3.51% 5.12%
Apr14 0.04% -1.75% 0.99%
Oct14 -0.22% -2.00% 1.72%
Fall2015 -0.28% -3.33% 0.81%
GFC Crash 0.08% -2.04% 3.49%
Recovery 0.09% -4.87% 7.01%
New Normal 0.02% -4.13% 3.63%